Listening to Trainee Concerns and Suggestions During COVID-19: a Report from the Canadian Consortium on Neurodegeneration in Aging (CCNA)
Bibliographic record
Abstract
Background The COVID-19 pandemic has caused significant disruption to research activities across Canada. The Training and Capacity Building (T&CB) Program of the Canadian Consortium on Neurodegeneration in Aging (CCNA) conducted a survey be-tween May 11th, 2020 and May 19th, 2020 to identify the chal-lenges faced by CCNA trainees because of the pandemic and how to best support trainees in response to those challenges. Methods Graduate students and postdoctoral researchers working under the supervision of CCNA investigators (n=113) were invited to complete a web-based survey of 13 questions. Trainees were asked questions about the impact of COVID-19 on their research activities, degree progression, funding status, and suggestions for support from the T&CB Program during the COVID-19 pandemic. Results A total of 41 trainees responded to the survey (response rate: 36.3%); 83% of respondents reported that they experienced changes to their research activities as a result of COVID-19, and 50% anticipated that their degree completion would be delayed. Respondents requested information from the T&CB Program on funding for non-COVID-19 projects, alternative datasets, and short educational workshops. Conclusion The majority of CCNA trainees surveyed experienced sig-nificant changes to their research activities as a result of the COVID-19 pandemic. The T&CB Program responded by switching to online programming and facilitating remote research. Further engagement with trainees is needed to ensure continued progress of research in age-related neurodegenera-tive disease in Canada post-pandemic.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".